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update model card README.md

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README.md ADDED
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+ ---
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+ language:
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+ - et
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+ license: apache-2.0
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+ tags:
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+ - whisper-event
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+ - generated_from_trainer
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+ datasets:
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+ - mozilla-foundation/common_voice_11_0
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: Whisper Medium et
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+ results:
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+ - task:
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+ name: Automatic Speech Recognition
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+ type: automatic-speech-recognition
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+ dataset:
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+ name: ERR2020, Common Voice 11.0, FLEURS
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+ type: mozilla-foundation/common_voice_11_0
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+ config: et
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+ split: test
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+ args: et
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+ metrics:
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+ - name: Wer
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+ type: wer
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+ value: 29.720322799236126
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # Whisper Medium et
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+
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+ This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the ERR2020, Common Voice 11.0, FLEURS dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4288
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+ - Wer: 29.7203
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 1e-06
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+ - train_batch_size: 32
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 64
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 500
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+ - training_steps: 5000
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Wer |
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+ |:-------------:|:-----:|:----:|:---------------:|:-------:|
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+ | 0.4018 | 0.1 | 500 | 0.5518 | 39.3951 |
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+ | 0.2654 | 0.2 | 1000 | 0.4611 | 34.3929 |
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+ | 0.2121 | 0.3 | 1500 | 0.4346 | 32.0582 |
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+ | 0.1752 | 0.4 | 2000 | 0.4247 | 31.1926 |
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+ | 0.1337 | 0.5 | 2500 | 0.4216 | 30.3364 |
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+ | 0.1281 | 0.6 | 3000 | 0.4219 | 30.0745 |
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+ | 0.1127 | 0.7 | 3500 | 0.4252 | 29.7388 |
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+ | 0.1254 | 0.8 | 4000 | 0.4276 | 29.8928 |
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+ | 0.1035 | 0.9 | 4500 | 0.4292 | 29.7634 |
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+ | 0.1114 | 1.0 | 5000 | 0.4288 | 29.7203 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.26.0.dev0
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+ - Pytorch 1.13.0+cu117
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+ - Datasets 2.7.1.dev0
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+ - Tokenizers 0.13.2
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